Penerapan Algoritma K-Medoids Untuk Pengelompokan Data Penerima Bantuan Uang Kuliah Tunggal Bagi Mahasiswa Terdampak Covid-19
-
Reza Andrea
*
Politeknik Pertanian Negeri Samarinda, Samarinda,
Indonesia
- Nursobah Nursobah STMIK Widya Cipta Dharma, Samarinda, Indonesia (*) Corresponding Author
Abstract
The ongoing Covid-19 pandemic period greatly affects various aspects of life, one of which is the issue of the economy. This problem has an impact on the field of education, one of which is at the university level. where many students whose parents/insurers of tuition fees are experiencing financial constraints due to the impact of the Covid-19 pandemic. So we need an effective way as a recommendation in analyzing student data based on the socioeconomic status of each student's parents in determining the group of UKT recipients. There are many ways that can be used, one of which is by utilizing data mining to group data for students who are entitled to get UKT using the K-Medoids method. The application of the K-Medoids method is used to group data on students who are eligible to receive UKT assistance funds with the aim of being a recommendation in analyzing student data based on the socioeconomic status of each student's parents in determining the UKT recipient group for the university. Whatever the results of the application of the K-medoids method, a group that deserves to be recommended is based on the results of Cluster / Grouping 0 with a total student data of 8 people based on the results of consideration of the criteria used, namely Parents' Occupation, Home Ownership Status and Parents' Income
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References
Z. Nabila, A. R. Isnain, Permata, dan Z. Abidin, “ANALISIS DATA MINING UNTUK CLUSTERING KASUS COVID-19 DI PROVINSI LAMPUNG DENGAN ALGORITMA K-MEANS,” J. Teknol. dan Sist. Inf., vol. 2, no. 2, hal. 100–108, 2021.
F. Firzada dan Y. Yunus, “Klasterisasi Tingkat Masa Studi Tepat Waktu Mahasiswa Menggunakan Algoritma K-Medoids,” J. Sistim Inf. dan Teknol., vol. 3, no. 3, hal. 160–166, 2021.
Y. R. A. Nugraha, “IMPLEMENTASI ALGORITME SUPPORT VECTOR MACHINE UNTUK KLASIFIKASI PENYESUAIAN UANG KULIAH TUNGGAL TERDAMPAK PANDEMI COVID-19,” J. Tek. Inform. Kaputama, vol. 5, no. 2, hal. 210–218, 2021.
E. Buulolo, R. Syahputra, dan A. Fau, “Algoritma K-Medoids Untuk Menentukan Calon Mahasiswa Yang Layak Mendapatkan Beasiswa Bidikmisi di Universitas Budi Darma,” J. MEDIA Inform. BUDIDARMA, vol. 4, no. 3, hal. 797–805, 2020.
J. Arianto, “PENERAPAN DATA MINING UNTUK PENGELOMPOKAN PENDUDUK KURANG MAMPU DESA SAMBIREJO TIMUR DENGAN ALGORITMA K-MEDOIDS,” KOMIK (Konferensi Nas. Teknol. Inf. dan Komputer), vol. 3, no. 1, hal. 569–573, 2019.
S. Defiyanti, M. Jajuli, dan N. R. W, “OptimalisasiK-Medoid Dalam Pengklasteran Mahasiswa Pelamar Beasiswa DenganCubic Clustering Criterion,” J. Nas. Teknol. Sist., vol. 3, no. 1, hal. 211–218, 2017.
N. Pulungan, Suhada, dan D. Suhendro, “PENERAPAN ALGORITMA K-MEDOIDS UNTUK MENGELOMPOKKAN PENDUDUK 15 TAHUN KEATAS MENURUT LAPANGAN PEKERJAAN UTAMA,” KOMIK (Konferensi Nas. Teknol. Inf. dan Komputer), vol. 3, no. 1, hal. 329–334, 2019.
F. Hardiyanti, H. S. Tambunan, dan I. S. Saragih, “PENERAPAN METODE K-MEDOIDS CLUSTERING PADA PENANGANAN KASUS DIARE DI INDONESIA,” KOMIK (Konferensi Nas. Teknol. Inf. dan Komputer), vol. 3, no. 1, hal. 598–603, 2019.
T. Juninda, Mustakim, dan E. Andri, “Penerapan Algoritma K-Medoids untuk Pengelompokan Penyakit di Pekanbaru Riau,” in Seminar Nasional Teknologi Informasi, Komunikasi dan Industri (SNTIKI) 11 Fakultas Sains dan Teknologi, UIN Sultan Syarif Kasim Riau, 2019, hal. 42–49.
R. Dirkareshza, D. M. Azura, dan R. Pradana, “Kebijakan Pemerintah di Masa Pandemi Covid-19: Antara Negara Sejahtera dan Negara Sehat,” J. Mercat., vol. 4, no. 1, hal. 46–55, 2021.
A. Wanto et al., Data Mining : Algoritma dan Implementasi. Medan: Yayasan Kita Menulis, 2020.
M. A. Puspa, “Implementasi Data Mining Klasifikasi Algoritma C4 . 5 Dalam Perekrutan Perangkat Desa,” Build. Informatics, Technol. Sci., vol. 1, no. 2, hal. 92–97, 2019.
Mariani, “Implementasi Algoritma Apriori Pada Persediaan Barang Minuman Larutan Cap Kaki Tiga ( Studi Kasus : PT Adyajati Lestari ),” Build. Informatics, Technol. Sci., vol. 1, no. 1, hal. 7–27, 2019.
D. Marlina, N. F. Putri, A. Fernando, dan A. Ramadhan, “Implementasi Algoritma K-Medoids dan K-Means untuk Pengelompokkan Wilayah Sebaran Cacat pada Anak,” J. CoreIT, vol. 4, no. 2, hal. 64–71, 2018.
S. Sundari, I. S. Damanik, A. P. Windarto, H. S. Tambunan, Jalaluddin, dan A. Wanto, “Analisis K-Medoids Clustering Dalam Pengelompokkan Data Imunisasi Campak Balita di Indonesia,” in Prosiding Seminar Nasional Riset Information Science (SENARIS), 2019, hal. 687–696.
Z. Mustofa dan I. S. Suasana, “ALGORITMA CLUSTERING K-MEDOIDS PADA E-GOVERNMENT BIDANG INFORMATION AND COMMUNICATION TECHNOLOGY DALAM PENENTUAN STATUS EDGI,” J. Teknol. Inf. dan Komun., vol. 9, no. 1, hal. 1–10, 2018.
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Pages: 632-638
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